code: def test_predict_with_both_input_data_and_path_raise(mock_backend):
      with pytest.raises(
          MlflowException,
          match=r"Both input_data and input_path are provided",
      ):
          mlflow.models.predict(
              model_uri="runs:/test/Model",
              input_data={"inputs": [1, 2, 3]},
              input_path="input.csv",
              content_type=_CONTENT_TYPE_CSV,
          )
  
file_path: mlflow/tests/models/test_python_api.py
imports: import datetime
  import sys
  from unittest import mock
  import numpy
  import pandas
  import pytest
  import scipy.sparse
  import mlflow
  from mlflow.exceptions import MlflowException
  from mlflow.models.python_api import _CONTENT_TYPE_CSV, _CONTENT_TYPE_JSON, _serialize_input_data
  from mlflow.utils.env_manager import CONDA, VIRTUALENV
label_desc: Use image node_id 4 for calling a global function with example usage: test_predict_with_both_input_data_and_path_raise(mock_backend) without return types